With the rapid development of high-speed and large-scale complex network, network vulnerability data presents the characteristics of massive, multi-source and heterogeneous, which makes data Floor Mats fusion become more complex.Although existing data fusion methods can fuse multi-source data, they do not consider that the multisource data may affect the accuracy of fusion result.To solve this problem, we propose an ontology and weighted D-S evidence theory-based vulnerability data fusion method.In our method, we utilize ontology to describe the network vulnerability semantically and construct the network vulnerability ontology hierarchically.
Then we use weighted D-S evidence theory to perform the operation of probability distribution and fusion processing.Besides, we simulate our method on MapReduce parallel computing platform.The AEG HKB95540NB 88cm Front Control Five Burner Gas-on-glass Hob experiment results show that our method is more effective and accurate compared with existing fusion approaches using single detection tool and traditional D-S evidence theory.